A histogram of gray levels provides an overall description of the appearance of an image. Properly adjusted gray levels for a given image can enhance the appearance or contrast thereof.
Among the many methods for contrast enhancement, the most widely known one is histogram equalization, in which the contrast of a given image is enhanced according to the sample distribution thereof. The method is disclosed in the following documents: 1! J. S. Lim, "Two-dimensional Signal and Image Processing," Prentice Hall, Englewood Cliffs, N.J., 1990, and 2! R. C. Gonzalez and P. Wints, "Digital Image Processing," Addison-Wesley, Reading, Mass., 1977.
Also, useful applications of the histogram equalization method, including medical image processing and radar image processing, are disclosed in the following documents: 3! J. Zimmerman, S. Pizer, E. Staab, E. Perry, W. McCartney and B. Brenton, "Evaluation of the Effectiveness of Adaptive Histogram Equalization for Contrast Enhancement," IEEE Tr. on Medical Imaging, pp. 304-312, December 1988, and 4! Y. Li, W. Wang and D. Y. Yu, "Application of Adaptive Histogram Equalization to X-ray Chest Image," Proc. of the SPIE, pp. 513-514, vol. 2321, 1994.
In general, since histogram equalization causes the dynamic range of an image to be expanded, the density distribution of the resultant image is made flat and the contrast of the image is enhanced as a consequence thereof.
This widely-known characteristic of histogram equalization is disadvantageous in some cases. That is, as the output density of the histogram equalization becomes uniform, the mean brightness of an output image approaches the middle gray level value. Actually, for the histogram equalization of an analog image, the mean brightness of the output image is exactly the middle gray level regardless of the mean brightness of the input image. It is obvious that this feature is not desirable in some real applications. For instance, an image taken at nighttime can appear to be an image taken in the daytime after histogram equalization has been performed. Meanwhile, too dark or too bright image signals result in a low contrast after the equalization.